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The U.S. Department of Energy Bioenergy Technology Office's (BETO's) 2023 Billion-Ton Report (BT23) is an assessment of renewable carbon resources potentially available in the United States. BT23 explores these resources in terms of quantity, price, geographical density and distribution, and market maturity. Resource quantities in this report are limited by specified economic and environmental sustainability constraints. Good practices are needed to ensure biomass production has positive environmental outcomes.

BT23 supports BETO's mission, particularly the 2023 Multi-Year Program Plan. To access 2023 Billion-Ton Report PDFs, appendices, and high-level messages, navigate to the 2023 Billion-Ton Report landing page at https://energy.gov/eere/bioenergy/2023-billion-ton-report-assessment-us… on the U.S. Department of Energy Bioenergy Technologies Office website.

To access information about the quality assumptions used in this report, please see the Biomass Feedstock Library at https://bioenergylibrary.inl.gov/Home/Home.aspx

Please cite the 2023 Billion-Ton Report as: U.S. Department of Energy. 2024. 2023 Billion‐Ton Report: An Assessment of U.S. Renewable Carbon Resources. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/SPR-2024/3103. doi: 10.23720/BT2023/2316165.

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This dataset includes POLYSYS model output prepared for BT23 Chapter 5. Please access the data through the BT23 Data Portal or directly at https://bioenergykdf.ornl.gov/bt23-agricultural-download

Please cite as:
Hellwinckel, C., D. de la Torre Ugarte, J. L. Field, and M. Langholtz. 2024, Data from Biomass from the Agricultural Land Base, of Chapter 5 in the 2023 Billion-Ton Report. Version 0.0.1, Bioenergy Knowledge Discovery Framework (bioenergyKDF) Data Center, https://doi.org/10.23720/BT2023/2282885

We present an updated estimate of potential biomass supplies from agricultural lands. The potential for farmers to respond to new markets for biomass has been assessed with the Policy Analysis System Model (POLYSYS) in previous versions of the billion-ton report (DOE 2017, 2016, 2011) and other studies (Oyedeji et al. 2021; Davis et al. 2020; Langholtz et al. 2019; Woodbury et al. 2018; Eaton, Langholtz, and Davis 2018; Langholtz et al. 2014; Langholtz et al. 2012; Jensen et al. 2007; De la Torre Ugarte and Ray 2000; Hellwinckel et al. 2015). Building on previous analyses, POLYSYS was used to update estimates of biomass supplies and prices from agricultural lands given environmental, land use, and technical constraints. The POLYSYS model, methods, and constraints are summarized in the chapter and detailed in the appendix. Changes from previous billion-ton reports include the use of the new 2023 USDA baseline, reporting of mature-market biomass supplies (see chapter Section 5.2: Methods Summary), oilseed supply estimates, and reporting of changes to carbon emissions and soil sequestration.

Note: Oilseed Crops have rotations and therefore may have duplicate rows by resource with differing production units. Users may sum these production numbers for aggregated data.

Note 2: Cotton gin trash and Rice hulls are downloaded separately and were not included in visualizations by resource.

This dataset includes ForSEAM and BioSUM model output prepared for BT23 Chapter 4, as well as USDA-FS Forest Inventory Analysis datasets used to calculate waste biomass from the forested land base. Please access the data through the BT23 Data Portal or directly at https://bioenergykdf.ornl.gov/bt23-forestry-download

Please cite as:
Davis, M., L. Lambert, R. Jacobson, C. Brandeis, J. Fried, B. English. 2024, Modeled Output and Other Data from Biomass from the Forested Land Base, of Chapter 4 in the 2023 Billion-Ton Report. Version 0.0.1, Bioenergy Knowledge Discovery Framework (KDF) Data Center, https://doi.org/10.23720/BT2023/2281324

A-customized-dataset-for-national-timberland-resources-modeled-with-ForSEAM

Test for future analysis (in development)

This dataset includes longitudinal measurements of water quality in four streams and rivers across the United States that were collected using the AquaBOT, an unmanned surface vehicle equipped with water quality sensors developed as part of a BETO-funded project ('Spatially resolved measurements of water quality indicators within a bioenergy landscape'). Measured water quality indicators include: nitrate concentration, temperature, specific conductivity, dissolved oxygen, turbidity, chlorophyll, and pH. The data can be found in the Excel file and details on the sampling sites, measurement methods, and data are available in the data guide.

These data are associated with the following paper:
Griffiths, N.A., P.S. Levi, J.S. Riggs, C.R. DeRolph, A.M. Fortner, and J.K. Richards. A sensor-equipped unmanned surface vehicle for high-resolution mapping of water quality in streams. Environmental Science & Technology Water. doi: 10.1021/acsestwater.1c00342

Simulations under this dataset were targeted to a specific fuelshed in Iowa.
Integrated land management (ILM) applications were targeted under this research, although the results of these simulations are at the county level; downscaling post-processing will be applied.

Short Rotation Woody Crop Production Scenarios Simulated for Idaho National Laboratory-ORNL Collaborations, June 2021.

This workshop examines the potential benefits, feasibility, and barriers to the use of biofuels in place of heavy fuel oil (HFO) and marine gas oil for marine vessels. More than 90% of world’s shipped goods
travel by marine cargo vessels powered by internal combustion (diesel) engines using primarily low-cost residual HFO, which is high in sulfur content. Recognizing that marine shipping is the largest source of
anthropogenic sulfur emissions and is a significant source of other pollutants including particulates, nitrogen oxides, and carbon dioxide (CO2), the International Maritime Organization enacted regulations to
lower the fuel sulfur content from 3.5 wt.% to 0.5 wt.% in 2020. These regulations require ship operators either to use higher-cost, low-sulfur HFO or to seek other alternatives for reducing sulfur emissions (i.e.,
scrubbers, natural gas, distillates, and/or biofuels). The near-term options for shipowners to comply with regulations include fueling with low-sulfur HFO or distillate fuels or installing emissions control systems.
However, few refineries are equipped to produce low-sulfur HFO. Likewise, the current production rates of distillates do not allow the necessary expansion required to fuel the world fleet of shipping vessels
(which consume around 330 million metric tons). This quantity is more than twice that used in the United States for cars and trucks. The other near-term option is to install emission control systems, which also
requires a significant investment. All of these options significantly increase operational costs. Because of such costs, biofuels have become an attractive alternative since they are inherently low in sulfur and
potentially also offer greenhouse gas benefits. Based on this preliminary assessment, replacing HFO in large marine vessels with minimally processed, heavy biofuels appears to have potential as a path to
reduced emissions of sulfur, CO2, and criteria emissions. Realizing this opportunity will require deeper knowledge of (1) the combustion characteristics of biofuels in marine applications, (2) their compatibility
for blending with conventional marine fuels (including HFO), (3) needs and costs for scaling up production and use, and (4) a systems assessment of their life cycle environmental impacts and costs. It is
recommended that a research program investigating each of these aspects be undertaken to better assess the efficacy of biofuels for marine use.

Contact information about the submitter of this metadata record:
Author list: Maggie Davis, Matt Langholtz, Laurence Eaton, Chad Hellwinkel
Who should be contacted with questions relating to the data? (Principal investigator or primary developer of data product): Maggie Davis, davismr@ornl.gov

What format is your data presented in? .csv .xls
Date data created 1/26-29/2016
Please include a description of the data set (abstract):
As part of the Billion Ton resource assessment projections created in 2016 (see https://www.energy.gov/sites/prod/files/2016/12/f34/2016_billion_ton_re…), this dataset was produced and titled a "base-case" scenario. This broader dataset provided an updated assessment of the potential economic availability of biomass resources from agricultural lands reported at the farmgate under conservative assumptions. Crop residues quantified in this dataset include corn stover, cereal (wheat, oats, and barley) straws, and sorghum stubble. We have isolated corn stover in this dataset.

What is the purpose of the data set? Why were the data collected?*
Per request for use in subsequent research, we have isolated corn stover in 2019 from the broader base-case projections and have provided tillage classification details from this projection. Tillage classification assumptions in this scenario allow a moderate deviation from a baseline situation (using historic CTIC data on tillage type used in counties for each crop). This dataset allowed moderate flexibility of farmers to put land into another tillage type (no till, conservation till, and reduced till) where a higher net present value was calculated.

Were data created or processed with a model or other analytical tool? Yes
Version POLYSYS v10_1-22-16b
Assumptions: Cumulative (energy crops and residues). Base-case (1% yield growth scenario), Tillage Flex = 1, across offered prices of $40-$60 in $5 increments from 2015 to 2040.

Should other organizations/individuals get credit for support, funding, or data collection and analysis? Yes, the USDOE BioEnergy Technologies Office (BETO) and the Oak Ridge National Laboratory (ORNL)